Publications by Method Matters

Accupedo vs. Fitbit Part 1: Convergent Validity of Hourly Step Counts with R

26.10.2019

In this post, we will investigate the relationship between hourly step count data from two different sources: the Accupedo app on my phone, the Fitbit I wear on my wrist. We will use several visualization and analytical techniques to understand the correspondence (or lack thereof) between the two measurements. Do these devices give similar readin...

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Exploratory Data Analysis of Cell Phone Usage with R: Part 1

17.11.2019

In this post, we will analyze data from my cell phone provider on my phone usage. The data contain information on my mobile data use, phone calls, and text messages. We will use exploratory data analysis to understand how my phone usage varies across the hours of the day, and examine whether the way I use my phone differs between weekdays and wee...

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Accupedo vs. Fitbit Part 2: Convergent Validity of Cumulative Step Counts with R

25.11.2019

This post is a continuation of the previous post on this blog. Last time, we analyzed hourly step count data from the Accupedo app on my phone, and from the Fitbit I wear on my wrist. This time, we will analyze the cumulative step count measurements taken from Accupedo and Fitbit. This metric is arguably more interesting from a user perspective. ...

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Exploratory Data Analysis of Cell Phone Usage with R: Part 2

13.12.2019

In this post, we will analyze data from my cell phone provider on my phone usage. In this post, we will focus on the volume of my mobile data use across time. We will use exploratory data analysis to understand how my usage of mobile data varies across the hours of the day, and examine whether the way I use my phone differs between weekdays and w...

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Creating an RSS Feed to Add Your Jekyll / Github Pages Blog to R-Bloggers

14.12.2019

In this post, we will go through the steps you need to follow if you would like to add a Jekyll / Github Pages blog to R-Bloggers. I recently went through this process and had to search through a lot of information in order to figure out how to do it. The process was particularly tricky because not all of the posts on my blog are about R (and the...

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Word Clouds for Management Presentations: A Workflow with R & Quanteda

07.06.2020

In this post, we’ll take a look at a basic text visualization technique we’ve seen elsewhere on this blog: word clouds. There are lots of great text analytics tools in R for this, and the process of making a basic word cloud is very straightforward. However, part of my job is providing data analysis and visualizations for senior management, a...

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Analyzing the Harmonic Structure of Music: Modes, Keys and Clustering Musical Genres

23.11.2020

In this post, we will examine the harmonic properties of songs in my music collection. We will focus on two primary aspects of the music: the mode (e.g. whether the songs are played in major or minor keys), and the musical key itself (e.g. C major, D minor, etc. – “tonal home” for the songs). Finally, we’ll explore differences across genr...

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Extracting Step Count, Heart Rate, and Activity Data From the Mi-Band 5: A Guide with Gadgetbridge and R

13.12.2020

In this post, we will see how to extract step count, heart rate, and activity data from the Xiaomi Mi-Band 5 tracking device. The Mi-Band 5 is a relatively inexpensive personal tracker that was released in July of 2020. I bought one in August after my Fitbit died (after 888 days of use). I considered buying another Fitbit, but was not very please...

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The Impact of the COVID-19 Pandemic on My Walking Behavior in 2020

25.01.2021

In this post, we will take a look back at 2020, and analyze my step count data to understand some of the impacts that the COVID-19 crisis had on my walking behavior during that crazy year. The Data Step Counts & Measurement Devices The step count data come from 2 sources in 2020 – I had a Fitbit for the first 8 months of the year, but it died i...

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How Do You Order Songs on an Album? Album Sequencing & Song Tempo Across Musical Genres

28.03.2021

In this post, we will return to a dataset we examined previously: information describing over 10,000 songs in my personal music collection. We’ll examine the tempo (e.g. the speed) at which songs are played, and analyze the tempo of songs across the length of an album – overall and separately for different musical genres. The goal is to bring...

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